Eli Whitney’s Cotton Gin is widely credited as a big driver of the industrial revolution and the economic success of early America, even though Whitney himself made little from the invention. Ford’s Model T in 1908 led to a massive shift towards mass production, and in turn, the roaring twenties. More recently, the prosperous Clinton years were fueled by the displacement of brick and mortar industries with their e-quivalents as the internet gained steam.

Even in the cases when the inventor did get rich off of their own invention, the real benefactors were their many peers who quickly adapted the new technology to suit their own purposes.

Today’s equivalent boom technology is mobile computing.

Like the desktop internet before it, the mobile revolution is easily mass produced. That doesn’t mean it’s easy to build a successful mobile company — that still requires the right expertise, first-mover advantage, and great execution. But it doesn’t require a once-in-a-generation stroke of genius, and that’s why the industry is able to move so quickly — strokes of genius don’t happen very often.

But like the roaring 20’s and the roaring 90’s, today’s roaring teens (at least in the technology community) won’t last forever. Once we’ve optimized every desktop application for mobile and taken advantage of every user’s geospatial information, we’ll have to come up with another new idea to drive tomorrow’s economy.

Of course, if I knew what this idea was, I’d have already invented it. But that doesn’t stop me from speculating on some likely areas to for the next big thing after mobile:

The SOA and Big Data movements have thoroughly whetted the corporate appetite for decision making based on analysis of large data sets. However, the ability to create this data is still very limited. In most cases, the data sets used by businesspeople rely on human interpretation of the real world (for example, a nurse inputs a person’s vital signs and demographic information into a console).

Using Artificial Intelligence, Visual Recognition, and Natural Language Processing technology, machines will continue to develop better ability to interpret real-world events without the aid of a human being. Imagine a technology that could scalably analyze every-day conversations in the same way that brands can mine Twitter. How many industries would that revolutionize?

As a person’s many identities across their network of applications converge and their actions gather ever more context, our understanding of human behavior will grow exponentially. By owning my browser, search history, and email account, for instance, Google understands how interactions with my personal network influence my other activity on the internet, and vise versa. Using the technology in #1, I expect my offline activities to be gradually integrated with this information to create a comprehensive picture of me and my behavior.

The main hurdle for progress in this field is privacy considerations, but if the past is any indication, economic benefits always win over privacy. People may be morally opposed to their cable operator analyzing their phone conversations, but that’s exactly what Google does with your emails, and nobody’s quitting Gmail. My bet is that consumer identities will continue to consolidate, and with it an ecosystem will develop around collection, analysis, and application of insights related to these identities.

3) Wireless Infrastructure Renewal

What’s the one thing that the cloud computing, big data, and mobile movements all have in common?

They all place tremendous pressure on network infrastructure:

Cloud applications rely much more on remote data and computing power than their on-premise counterparts.

Big data means more information is stored and transmitted for any given action. The total volume of data stored globally doubles about once every two years.

Let’s assume that global smartphone penetration is right now at 15%, and 10% of the bandwidth you use comes through mobile (versus broadband). In five years, if these numbers are 90% and 50%, respectively, and the total volume of data is 10x as high, will the same infrastructure be able to handle it?

My guess is no.

That means that network infrastructure, which has been an unsexy business since the industry over-expanded in the late 1990’s, will be under tremendous pressure to keep up with the demands of a supercharged mobile internet. As always, with tremendous pressure comes tremendous rewards.

Sign-up for our Free Weekly Newsletter to get the best new ideas for building technology companies.